def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'honour'
data['_template'] = 'honour.html'
# filename, title, headline and update date for this
data['title'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['TITLE']))
data['headline'] = htmlparser.parse(datasheet['HEADLINE'],
datasheet['FILENAME'],
paragraphs=False,
url_context=url_context)
# parse biography
data['content'] = htmlparser.parse(datasheet['CONTENT'],
datasheet['FILENAME'],
paragraphs=True,
url_context=url_context)
data['tags'] = ''
# alphabetical display entries
parsed_entries = []
if data['title'].strip() != '':
s = data['title'].strip()
parsed_entries.append(s)
elif data['headline'].strip() != '':
s = data['headline'].strip()
parsed_entries.append(s)
data['alphabetical'] = '\n'.join(parsed_entries)
return data
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'quotation'
data['_template'] = 'quotation.html'
# filename, name
data['name'] = symbolreplace.tags_to_unicode(datasheet['NAME'])
content = datasheet['CONTENT']
numquotes = datasheet['NUMQUOTES']
# special case cleaning rules
if datasheet['FILENAME'] == 'Carmichael':
content = content.replace('<p>', '')
if datasheet['FILENAME'] in NUMBER_CORRECTIONS:
numquotes = NUMBER_CORRECTIONS[datasheet['FILENAME']]
# now parse the individual quotes
content = content.split('<p>')
quotes = []
for quote in content:
if quote.strip() != '':
quotes.append(quote.strip())
# holding 'more quotes' links, or 'translations by'
data['more'] = ''
if len(quotes) != 0 and 'More ' in quotes[-1] and '<a href' in quotes[-1]:
#print('I *think* this is a *more quotes* paragraph:', quotes[-1])
data['more'] = quotes.pop()
if len(quotes) != 0 and data['more'] == '' and 'Translations ' in quotes[-1]:
#print('I *think* this is a *translations by* paragraph:', quotes[-1])
data['more'] = quotes.pop()
if len(quotes) != int(numquotes):
print('ERROR', len(quotes), 'expcting', int(numquotes))
print(quotes)
assert False
# now parse the quotes and convert to html
for idx, quote in enumerate(quotes):
q = parse_quote(quote)
q['quote'] = htmlparser.parse(q['quote'], 'Quotations/%s' % datasheet['FILENAME'], paragraphs=True, url_context=url_context)
q['source'] = htmlparser.parse(q['source'], 'Quotations/%s' % datasheet['FILENAME'], paragraphs=False, url_context=url_context)
quotes[idx] = q
quotations = flow.to_flow_block('quotation', quotes)
data['quotations'] = quotations
return quotations
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'page'
data['_template'] = 'page.html'
# sidebar
data['sidebar'] = ''
# easily translatable info
data['authors'] = htmlparser.parse(datasheet['WHODIDIT'], datasheet['FILENAME'], paragraphs=False, url_context=url_context)
data['title'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['TITLE']))
# check that this is a standard page
#assert datasheet['USEHTMLFORMAT'] == 'Y'
# need to convert it to a standard page
content = datasheet['CONTENT']
regex = re.compile(r'<html>(?P<content>.*?)</html>', re.MULTILINE | re.DOTALL)
content = re.sub(regex, strip, content)
regex = re.compile(r'<head>(?P<content>.*?)</head>', re.MULTILINE | re.DOTALL)
content = re.sub(regex, strip_all, content)
regex = re.compile(r'<title>(.*?)</title>', re.MULTILINE | re.DOTALL)
content = re.sub(regex, r'', content)
regex = re.compile(r'<meta (.*?)/>', re.MULTILINE | re.DOTALL)
content = re.sub(regex, r'', content)
regex = re.compile(r'<style>(.*?)</style>', re.MULTILINE | re.DOTALL)
content = re.sub(regex, r'', content)
regex = re.compile(r'<body(.*?)>', re.MULTILINE | re.DOTALL)
content = re.sub(regex, r'', content)
content = content.replace('</body>', '')
content = content.strip()
# also get rid of the 'show larger image' button
regex = re.compile(r'<form>(.*?)</form>', re.MULTILINE | re.DOTALL)
content = re.sub(regex, r'', content)
# parse biography, and add in extras and translations
data['content'] = htmlparser.parse(content,
datasheet['FILENAME'],
paragraphs=True,
url_context=url_context)
return data
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'curve'
data['_template'] = 'curve.html'
# easily translatable info
data['name'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['FULLNAME']))
# need to parse the individual equations out, and convert to flow
equations = parse_equations(datasheet['EQUATIONS'], datasheet['FILENAME'])
data['equations'] = flow.to_flow_block('curveequation', equations)
# parse java applet options
options = '{\n'
pattern = re.compile(
r'\<PARAM NAME="(?P<name>.+?)" VALUE="(?P<value>.+?)">')
for match in re.finditer(pattern, datasheet['JAVA']):
name = match.group('name')
value = match.group('value')
line = '%s: "%s",\n' % (name, value)
options += line
options += '}'
data['appletoptions'] = options
# parse content
data['content'] = htmlparser.parse(datasheet['CONTENTS'],
datasheet['FILENAME'],
paragraphs=True,
url_context=url_context)
return data
def parse_cross_references(references, name, url_context):
parsed = []
for line in references.splitlines():
line = line.strip()
# match against reference line
#bio_regex = re.compile(r'^(?P<number>\d+)\s*,\s*(?P<link>.+?)\s*,\s*(?P<text>.+?)(?:,\s*(?P<extratext>.+?))?$')
bio_regex = re.compile(
r'^(?P<number>\d+)\s*,\s*(?P<link>.+?)\s*(?:,\s*(?P<text>.+?))?(?:,\s*(?P<extratext>.+?))?$'
)
match = re.match(bio_regex, line)
if match:
# this is a reference line
number = match.group('number')
link = match.group('link')
text = match.group('text')
if not text:
text = 'THIS LINK'
link = urls.convert(link, url_context)
if match.group('extratext'):
text += ' ' + match.group('extratext')
text = text.strip()
if not text:
text = link
else:
text = htmlparser.parse(text, name)
reference = {'link': link, 'text': text, 'number': number}
parsed.append(reference)
continue
return_str = {'data': parsed}
return_str = json.dumps(return_str)
return return_str
def parse_references(references, name, url_context):
parsed_references = []
in_reference = False
reference = None
for line in references.splitlines():
line = line.strip()
# match against reference line
bio_regex = re.compile(r'^(?P<number>\d+)\s*,\s*(?P<reference>.+)$')
match = re.match(bio_regex, line)
if match:
# this is a reference line
reference = match.group('reference')
number = match.group('number')
ref = {'number': number, 'reference': reference.strip()}
parsed_references.append(ref)
in_reference = True
continue
# match against url
if (line.startswith('http://')
or line.startswith('https://')) and in_reference:
# check there's not an issue with the line
assert '<' not in line and '>' not in line
# make the entire reference a link
href = line
href = urls.convert(href, url_context)
text = parsed_references[-1]['reference']
text = text.replace('<br>', '')
'''link = '<a href="%s">%s</a>' % (href, text)
# only do this if there isn't already a link in the reference
if '<a' not in text:
parsed_references[-1]['reference'] = link'''
parsed_references[-1]['reference'] = '%s <a href="%s">%s</a>' % (
text, href, href)
in_reference = False
# match against empty line
if line == '' or '<p>' in line:
in_reference = False
continue
# any other line
if in_reference:
parsed_references[-1]['reference'] += (' ' + line.strip())
for reference in parsed_references:
reference['reference'] = htmlparser.parse(reference['reference'], name)
return_str = {'data': parsed_references}
return_str = json.dumps(return_str)
return return_str
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'extra'
data['_template'] = 'extra.html'
# filename, title, headline and update date for this
data['title'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['TITLE']))
data['headline'] = htmlparser.parse(datasheet['HEADLINE'], datasheet['FILENAME'], paragraphs=False, url_context=url_context)
data['update'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['UPDATE']))
# parse references
references = referenceparser.parse_references(datasheet['REFERENCES'], datasheet['FILENAME'], url_context)
data['references'] = flow.to_flow_block('reference', json.loads(references)['data'])
# parse biography
data['content'] = htmlparser.parse(datasheet['EXTRA'],
datasheet['FILENAME'],
paragraphs=True,
url_context=url_context)
return data
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'obituary'
data['_template'] = 'obituary.html'
# easily translatable info
data['name'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['HEADING1']))
data['summary'] = htmlparser.parse(datasheet['HEADING2'],
datasheet['FILENAME'],
paragraphs=False,
url_context=url_context)
data['wherefrom'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['TITLE']))
# parse biography, and add in extras and translations
data['content'] = htmlparser.parse(datasheet['CONTENT'],
datasheet['FILENAME'],
paragraphs=True,
url_context=url_context)
return data
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'glossary'
data['_template'] = 'glossary.html'
# easily translatable info
data['term'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['WORD']))
# parse biography, and add in extras and translations
data['content'] = htmlparser.parse(datasheet['CONTENTS'],
datasheet['FILENAME'],
paragraphs=True,
url_context=url_context)
return data
def chronology_convert(input_dir, output_dir, url_context):
# get all the files that need to be processed
path = os.path.join(input_dir, '*')
files = glob.glob(path)
dates = {}
# process all the files
for file in files:
# parse sections from datasheet
datasheet = datasheetparser.parse_file(file)
date = datasheet['DATE']
content = htmlparser.parse(datasheet['BIG'],
os.path.basename(file),
paragraphs=False,
url_context=url_context)
data = {
'about': 'yes' if datasheet['ABOUT'] != '' else 'no',
'content': content
}
if date not in dates:
dates[date] = []
dates[date].append(data)
# convert to nested flow
chronology = []
for date, events in dates.items():
data = {
'_model': 'chronologyyear',
'_hidden': 'yes',
'year': date,
'events': flow.to_flow_block('chronology-event', events)
}
filename = os.path.join(LEKTOR_CONTENT_PATH, output_dir, date)
save(data, filename)
def parse_equations(text, filename):
equations = []
eqtype = None
typeregex = re.compile(
r'^<b><font color=green>(?P<type>.+?)</font></b>.*$')
equationregex = re.compile(r'^(?P<equation>\\.+?\\\\)$')
text = text.split('\n')
for line in text:
line = line.strip()
typematch = typeregex.search(line)
equationmatch = equationregex.search(line)
if typematch:
# it's a type!
assert eqtype == None
eqtype = typematch.group('type')
elif equationmatch:
# it's an equation!
assert eqtype
eqtype = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(eqtype))
equation = {
'type':
eqtype,
'equation':
htmlparser.parse(equationmatch.group('equation'),
filename,
paragraphs=False)
}
eqtype = None
equations.append(equation)
else:
assert False
return equations
def read_logs():
msg = servicehandler.getlogs()
return htmlparser.parse(msg)
def project_convert(input_dir, output_dir, url_context, name):
# get all the files that need to be processed
path = os.path.join(input_dir, '*')
files = glob.glob(path)
titles = {
'Ayel': 'The French Grandes Ecoles',
'Brunk': 'The development of Galois theory',
'Burslem': 'Sofia Kovalevskaya',
'Daxenberger':
'Johan de Witt - The first calculation on the valuation of life annuities',
'Ellison': 'Sofia Kovalevskaya',
'Johnson': 'James Clerk Maxwell - The Great Unknown',
'MacQuarrie': 'Mathematics and Chess',
'Pearce': 'Indian Mathematics - Redressing the balance',
'Watson': 'Some topics in the history of mathematical education',
'Ledermann': 'Walter Ledermann - Encounters of a Mathematician',
'DickinsonCernokova':
"An investigation of some of D'Arcy Thompson's correspondence",
'GowenlockTuminauskaite': "D'Arcy Thompson and Mathematics"
}
authors = {
'Ayel': 'Mathieu Ayel',
'Brunk': 'Fiona Brunk',
'Burslem': 'Tom Burslem',
'Daxenberger': 'Livia Daxenberger',
'Ellison': 'Leigh Ellison',
'Johnson': 'Kevin Johnson',
'MacQuarrie': 'John MacQuarrie',
'Pearce': 'Ian G Pearce',
'Watson': 'Helen Watson',
'Ledermann': "J J O'Connor and E F Robertson",
'DickinsonCernokova': 'Heather Dickinson and Barbora Cernokova',
'GowenlockTuminauskaite': 'Alice Gowenlock and Indre Tuminauskaite'
}
pages = []
references = ''
# process all the files
for file in files:
# parse sections from datasheet
datasheet = datasheetparser.parse_file(file)
if datasheet['NUMBER'] == 'refs' and 'REFERENCES' in datasheet:
# this is the references, not a page
references = referenceparser.parse_references(
datasheet['REFERENCES'], file, url_context)
references = flow.to_flow_block('reference',
json.loads(references)['data'])
continue
pagenum = int(datasheet['NUMBER'])
assert pagenum == len(pages)
content = cleaning.project_cleaning(datasheet['CONTENT'])
data = {
'_model':
'projectpage',
'_template':
'projectpage.html',
'title':
datasheet['TITLE'],
'content':
htmlparser.parse(content,
file,
paragraphs=True,
url_context=url_context),
'chapter':
str(len(pages) + 1)
}
pages.append(data)
# main project page
data = {
'_model': 'project',
'_template': 'project.html',
'title': titles[name],
'author': authors[name],
'references': '' if references is None else references
}
filename = os.path.join(LEKTOR_CONTENT_PATH, output_dir)
save(data, filename)
# the chapters
for page in pages:
filename = os.path.join(LEKTOR_CONTENT_PATH, output_dir,
'chapter-%s' % page['chapter'])
save(page, filename)
print('processed', name)
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'historytopic'
data['_template'] = 'historytopic.html'
# filename, short and full name, authors, update
data['shortname'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['SHORTNAME']))
data['fullname'] = htmlparser.parse(datasheet['FULLNAME'],
datasheet['FILENAME'],
paragraphs=False,
url_context=url_context)
data['authors'] = htmlparser.parse(datasheet['AUTHORS'],
datasheet['FILENAME'],
paragraphs=False,
url_context=url_context)
data['update'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['UPDATE']))
# something about indexes, not sure how this is used yet
data['indexref'] = datasheet['INDEXREF']
data['indexreffile'] = datasheet['INDEXREFFILE']
# parse references
references = referenceparser.parse_references(datasheet['REFERENCES'],
datasheet['FILENAME'],
url_context)
data['references'] = flow.to_flow_block('reference',
json.loads(references)['data'])
# parse additional links (they use the same format as cross references)
additional = referenceparser.parse_cross_references(
datasheet['ADDITIONAL'], datasheet['FILENAME'], url_context)
data['additional'] = flow.to_flow_block('otherweb',
json.loads(additional)['data'])
# parse translations (use the same format as references)
# don't add them to data, as we're combining them with bio
translations = referenceparser.parse_references(datasheet['TRANSLATION'],
datasheet['FILENAME'],
url_context)
translation_data = json.loads(translations)['data']
translation_data = [{
'number': d['number'],
'translation': d['reference']
} for d in translation_data]
data['translations'] = flow.to_flow_block('translation', translation_data)
# parse otherweb links (they use the same format as cross references)
otherweb = referenceparser.parse_cross_references(datasheet['OTHERWEB'],
datasheet['FILENAME'],
url_context)
data['otherweb'] = flow.to_flow_block('otherweb',
json.loads(otherweb)['data'])
# parse history topic
data['content'] = htmlparser.parse(
datasheet['HISTTOPIC'],
datasheet['FILENAME'],
translations=json.loads(translations)['data'],
extras=json.loads(additional)['data'],
paragraphs=True,
url_context=url_context)
# discover categories for this mathematician
path = '/HistTopics/%s' % datasheet['FILENAME']
tags = []
#with open('../datasheets/Indexes/data.json') as f:
# category_data = json.load(f)
category_data = categories.categories()
for category in category_data:
if path in category['entries']:
tags.append(category['name'])
data['tags'] = ', '.join(tags)
# discover alphabetical index names for this history topic
parsed_entries = []
if 'INDEXNAMES' not in datasheet:
if data['fullname'].strip() != '':
parsed_entries.append(data['fullname'].strip())
elif data['shortname'].strip() != '':
parsed_entries.append(data['shortname'].strip())
else:
print('no names for this topic')
assert False
else:
entries = datasheet['INDEXNAMES'].strip().split('\n')
for entry in entries:
entry = entry.strip()
entry = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(entry))
parsed_entries.append(entry)
data['alphabetical'] = '\n'.join(parsed_entries)
return data
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'biography'
data['_template'] = 'biography.html'
# name and shortname
data['shortname'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['SHORTNAME']))
data['fullname'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['FULLNAME']))
# authors
data['authors'] = htmlparser.parse(datasheet['AUTHORS'], datasheet['FILENAME'], paragraphs=False, url_context=url_context)
# last update
data['update'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['UPDATE']))
data['summary'] = htmlparser.parse(datasheet['SUMMARY'], datasheet['FILENAME'], paragraphs=False, url_context=url_context)
# dates are tricky. for now leave them as they are
data['birthdate'] = datasheet['BIRTHDATE']
data['deathdate'] = datasheet['DEATHDATE']
# birth and death year - remove the ,? if necessary
date_pattern = re.compile(r'(\d+)(?:,\??)?')
data['birthyear'] = re.sub(date_pattern, r'\1', datasheet['BIRTHYEAR'])
data['deathyear'] = re.sub(date_pattern, r'\1', datasheet['DEATHYEAR'])
# birthplace, deathplace
data['birthplace'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['BIRTHPLACE']))
data['deathplace'] = symbolreplace.strip_tags(symbolreplace.tags_to_unicode(datasheet['DEATHPLACE']))
# mapinfo - just take the name, ignore mapnum and lat/long
mapinfo = re.compile(r'\d,(?P<name>.+?),(?:(?P<lat>-?[\d.]+),(?P<long>-?[\d.]+))?')
match = mapinfo.search(datasheet['MAPINFO'])
data['maplocation'] = '--Unknown--'
data['maplocation'] = ''
if match:
data['maplocation'] = match.group('name')
# country
data['country'] = '--Unknown--'
if datasheet['COUNTRY'].strip() != '':
data['country'] = datasheet['COUNTRY']
if data['country'] == 'Czech_Republic':
data['country'] = 'Czech Republic'
elif data['country'] == 'Sicily':
data['country'] = 'Italy'
elif data['country'].endswith(')'):
data['country'] = data['country'][:-1]
elif data['country'] == '':
data['country'] == '--Unknown--'
# also add countries to global array
if not data['country'] in countries:
countries.append(data['country'])
# parse references
references = referenceparser.parse_references(datasheet['REFERENCES'], datasheet['FILENAME'], url_context)
data['references'] = flow.to_flow_block('reference', json.loads(references)['data'])
# parse translations (use the same format as references)
# don't add them to data, as we're combining them with bio
translations = referenceparser.parse_references(datasheet['TRANSLATION'], datasheet['FILENAME'], url_context)
translation_data = json.loads(translations)['data']
translation_data = [{'number':d['number'],'translation':d['reference']} for d in translation_data]
data['translations'] = flow.to_flow_block('translation', translation_data)
# parse cross references
#xrefs = referenceparser.parse_cross_references(datasheet['XREFS'], datasheet['FILENAME'])
#data['xrefs'] = xrefs
# parse additional links (they use the same format as cross references)
# don't add them to data, as we're combining them with bio
additional = referenceparser.parse_cross_references(datasheet['ADDITIONAL'], datasheet['FILENAME'], url_context)
data['additional'] = flow.to_flow_block('otherweb', json.loads(additional)['data'])
# parse otherweb links (they use the same format as cross references)
otherweb = referenceparser.parse_cross_references(datasheet['OTHERWEB'], datasheet['FILENAME'], url_context)
data['otherweb'] = flow.to_flow_block('otherweb', json.loads(otherweb)['data'])
# parse honours links (they use the same format as cross references)
honours = referenceparser.parse_cross_references(datasheet['HONOURS'], datasheet['FILENAME'], url_context)
data['honours'] = flow.to_flow_block('otherweb', json.loads(honours)['data'])
# parse biography, and add in extras and translations
data['content'] = htmlparser.parse(datasheet['BIOGRAPHY'],
datasheet['FILENAME'],
translations=json.loads(translations)['data'],
extras=json.loads(additional)['data'],
paragraphs=True,
url_context=url_context)
# discover categories for this mathematician
path = '/Biographies/%s' % datasheet['FILENAME']
tags = []
#with open('../datasheets/Indexes/data.json') as f:
# category_data = json.load(f)
category_data = categories.categories()
for category in category_data:
if path in category['entries']:
tags.append(category['name'])
data['tags'] = ', '.join(tags)
# discover alphabetical tags for this mathematician
displays = alphaindexparser.get_displays_2(datasheet['FILENAME'])
if not displays:
assert False
displays = '\n'.join(displays)
data['alphabetical'] = displays
return data
def get_dom(self): return htmlparser.parse(self.file.read())
continue
pattern = re.compile(r'^(?P<position>[SCLR]),(?P<path>.+?),(?P<height>.+?)(?:,(?P<description>.*))?$')
match = pattern.search(line)
if not match:
print('not a match! (%s), (%s)' % (name, line))
assert False
position = match.group('position')
path = match.group('path')
height = match.group('height')
description = match.group('description') or ''
description = strip_br(description)
# parse the description
description = htmlparser.parse(description,
'PictDisplay/%s' % name,
paragraphs=False,
url_context='PictDisplay/%s' % name)
description = strip_br(description)
# check this person exists
biography_dir = os.path.join(CONTENT_DIR, 'Biographies/', name)
if not os.path.isdir(biography_dir):
with open('not-exists.txt', 'a') as f:
f.write('%s\n' % name)
continue
# copy that image in
img_dst = os.path.join(biography_dir, os.path.basename(path))
img_src = os.path.join(SERVER_FILES, path)
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'society'
data['_template'] = 'society.html'
# easily translatable info
data['name'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['TITLENAME']))
data['headline'] = htmlparser.parse(datasheet['HEADLINE'],
datasheet['FILENAME'],
paragraphs=False,
url_context=url_context)
data['update'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['UPDATE']))
data['foundation'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['FOUNDATION']))
# external site parsing
link = re.compile(
r'<a\s+href ?= ?[\'"]?(?P<href>.+?)[\'"]?\s*>(?P<text>.*?)<\/a>')
if datasheet['OTHERWEB'].strip() == '':
data['website'] = ''
else:
match = link.search(datasheet['OTHERWEB'].strip())
if not match:
print('not link "%s"' % datasheet['OTHERWEB'].strip())
assert match
data['website'] = match.group('href')
# parse references
references = referenceparser.parse_references(datasheet['REFERENCES'],
datasheet['FILENAME'],
url_context)
data['references'] = flow.to_flow_block('reference',
json.loads(references)['data'])
# parse additional links (they use the same format as cross references)
# don't add them to data, as we're combining them with bio
additional = referenceparser.parse_cross_references(
datasheet['EXTRAS'], datasheet['FILENAME'], url_context)
data['additional'] = flow.to_flow_block('otherweb',
json.loads(additional)['data'])
# parse biography, and add in extras and translations
data['content'] = htmlparser.parse(datasheet['CONTENT'],
datasheet['FILENAME'],
extras=json.loads(additional)['data'],
paragraphs=True,
url_context=url_context)
data['tags'] = ''
# alphabetical display entries
parsed_entries = []
if data['name'].strip() != '':
s = data['name'].strip()
parsed_entries.append(s)
elif data['headline'].strip() != '':
s = data['headline'].strip()
parsed_entries.append(s)
data['alphabetical'] = '\n'.join(parsed_entries)
return data
def convert(datasheet, url_context):
data = {}
# metadata, the template and model
data['_model'] = 'gazplace'
data['_template'] = 'gazplace.html'
data['place'] = symbolreplace.strip_tags(
symbolreplace.tags_to_unicode(datasheet['TITLE']))
pattern = re.compile(r'(?P<lat>-?[\d.]+),(?P<long>-?[\d.]+)')
match = pattern.search(datasheet['COORDS'])
data['latitude'] = ''
data['longitude'] = ''
if match:
data['latitude'] = match.group('lat')
data['longitude'] = match.group('long')
# i was an idiot, and made a mistake in generating the datasheets for GazData
# the correct CONTENTS is in GazData3
# so we have to read that instead
path = os.path.join('../datasheets/GazData3/', datasheet['FILENAME'])
datasheet2 = datasheetparser.parse_file(path)
# convert the references to the new style of references
refcount = 1
parsed_references = []
references = datasheet['REFERENCES'].strip().split('\n')
for reference in references:
reference = reference.strip()
if reference == '':
continue
parts = reference.split('@')
if len(parts) != 3:
print(reference)
assert len(parts) == 3
replacement = parts[0].strip()
text = parts[2].strip()
if replacement not in datasheet2['CONTENTS']:
print(reference)
assert replacement in datasheet2['CONTENTS']
datasheet2['CONTENTS'] = datasheet2['CONTENTS'].replace(
replacement, '[%s]' % refcount)
parsed_references.append({
'number':
str(refcount),
'reference':
htmlparser.parse(text, datasheet['FILENAME'])
})
refcount = refcount + 1
data['references'] = flow.to_flow_block('reference', parsed_references)
# parse biography, and add in extras and translations
data['content'] = htmlparser.parse(datasheet2['CONTENTS'],
datasheet['FILENAME'],
paragraphs=True,
url_context=url_context)
if data['place'] == 'Whitburn, Tyne & Wear':
# add in the missing lat and long
data['latitude'] = '54.9550395'
data['longitude'] = '-1.3867149'
if data['latitude'] == '' and data['longitude'] == '':
# this is not a place, it should just be a page
newdata = {}
newdata['_model'] = 'page'
newdata['_template'] = 'gazplace.html'
newdata['title'] = data['place']
newdata['authors'] = ''
newdata['content'] = data['content']
return newdata
return data
